Large Language Models and Applications

A special issue of AppliedMath (ISSN 2673-9909).

Deadline for manuscript submissions: 30 July 2026 | Viewed by 23

Special Issue Editors


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Guest Editor
Faculty of Engineering, University of Kragujevac, 34000 Kragujevac, Serbia
Interests: artificial intelligence; various AI applications; cybersecurity; communication systems; software modeling; design and development

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Guest Editor
Faculty of Diplomacy and Security, University Union—Nikola Tesla, Belgrade, Serbia
Interests: information technology
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Guest Editor
Department for Industrial Engineering, Faculty of Engineering, University of Kragujevac, Sestre Janjić 6, 34000 Kragujevac, Serbia
Interests: industrial engineering; operational research; engineering management; reliability engineering; FMEA
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to submit your research to be considered for publication in a Special Issue of AppliedMath, focused on the latest advances in Large Language Models (LLMs) and their applications. The goal of this Special Issue is to showcase state-of-the-art research in this fast-evolving field and to provide a platform for researchers and practitioners to share their most promising findings.

Large Language Models (LLMs) have become a transformative force in artificial intelligence and data-driven technologies. They enable breakthroughs in natural language processing, knowledge representation, reasoning, and human–machine interaction. From scientific research to real-world engineering applications, LLMs are being integrated into domains such as healthcare, education, finance, cybersecurity, and smart cities, where their potential to revolutionize decision making and problem solving is profound.

In this Special Issue, we invite and welcome reviews and original research papers addressing both the theoretical foundations and practical implementations of LLMs. Topics of interest include, but are not limited to, the following: novel architectures, efficient training and inference techniques, domain-specific adaptations, multimodal integration, evaluation methods, ethical and trustworthy AI, and innovative real-world applications of LLMs in science, industry, and society.

Dr. Milan Čabarkapa
Prof. Dr. Dragan Ranđelović
Dr. Nikola Komatina
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AppliedMath is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • large language models (LLMs)
  • generative AI
  • natural language processing (NLP)
  • transformer architectures
  • pre-trained models
  • fine-tuning and adaptation
  • multimodal models
  • prompt engineering
  • retrieval-augmented generation (RAG)
  • knowledge representation
  • human–AI interaction
  • explainable AI (XAI)
  • ethical and trustworthy AI
  • bias and fairness in AI
  • scalable training and inference
  • federated and distributed learning
  • domain-specific applications
  • healthcare AI
  • financial AI
  • education technology
  • cybersecurity applications
  • smart cities and IoT integration
  • robotics and autonomous systems
  • evaluation benchmarks and metrics
  • real-world deployments

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Published Papers

This special issue is now open for submission.
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